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Armchair Architects: LLMs & Vector Databases (Part 1)
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2023Dec 12
Vector databases are designed to store, manage, and index massive quantities of high-dimensional vector data efficiently that can help different types of queries, such as nearest neighbor. In this episode of the #AzureEnblementShow, Uli, Eric (‪@mougue‬) and David discuss how vector databases convert data to integers, cover some of the use cases of vector databases, and the benefits of embedding. This is part one of a two-part series. Resources • Vector search in Azure AI Search https://learn.microsoft.com/en-us/azu... • Geospatial data processing and analytics https://learn.microsoft.com/en-us/azu... • Microsoft Azure AI Fundamentals: Natural Language Processing https://learn.microsoft.com/en-us/tra... • Azure Database for PostgreSQL https://learn.microsoft.com/en-us/tra... • Vector DB Lookup tool for flows in Azure AI Studio https://learn.microsoft.com/en-us/azu... Related episodes • Armchair Architects: LLMs & Vector Databases (Part 2) https://aka.ms/azenable/142 • Watch more episodes in the Armchair Architects Series https://aka.ms/azenable/ArmchairArchi... • Watch more episodes in the Well-Architected Series https://aka.ms/azenable/yt/wa-playlist Chapters 0:00 Introduction 0:38 Data stored as integers 1:30 Text converted to numerical data 2:29 Vectors are not new 3:47 Use cases 5:02 Benefits of Embedding 7:40 Vectorizing semantic concepts 8:38 Teaser for Part 2

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Microsoft Developer

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